Human papillomavirus is detected in transitional cell carcinoma arising in renal transplant recipients

"This is a non-final version of an article published in final form in Pathology The Journal of the Royal College of Pathologists of Australasia 41 (3) pp.245-247"Aims: We investigated the role of human papillomavirus HPV in the development of transitional cell carcinoma TCC arising in renal transplant recipients. Methods: Genomic DNA was extracted from 10 m paraffin embedded sections of five TCCs arising in five renal transplant recipients using the QIAamp DNA mini kit according to the manufacturer's instructions. β-globin PCR was performed to test DNA adequacy. Samples were tested for the presence of HPV DNA by broad spectrum HPV PCR method using non-biotinylated SPF10 primers SPF1A, SPF1B, SPF1C, SPF1D, SPF2B, SPF2D which amplify a short 65 bp fragment. Positive bands were identified on a 3 gel. Positive samples underwent a second HPV PCR and were amplified using biotinylated SPF10 primer set, which amplifies the same 65 bp region of the L1 open reading frame. INNO-LiPA line probe assay was then performed to genotype the samples which uses a reverse hybridisation principle. Results: Four of five TCCs examined were positive for HPV. The high risk HPV16 was detected in three cases whereas in the fourth case an unclassifiable HPV genotype was present. In all DNA samples, β-globin amplification was successful. Conclusions: Our results indicate that HPV and in particular HPV16 may play an aetiological role in the development of TCC in renal transplant patients.Peer reviewedSubmitted Versio

q-Space Imaging Yields a Higher Effect Gradient to Assess Cellularity than Conventional Diffusion-weighted Imaging Methods at 3.0 T : A Pilot Study with Freshly Excised Whole-Breast Tumors

N.S. supported by Biotechnology and Biological Sciences Research Council (1654748, BB/M010996/1). Study supported by the National Health Service Grampian Endowment Fund (15/1/052).Peer reviewedPublisher PD

Intra-tumoural lipid composition and lymphovascular invasion in breast cancer via non-invasive magnetic resonance spectroscopy

Acknowledgements The authors would like to thank Dr. Nicholas Senn for conducting data auditing, Dr. Matthew Clemence (Philips Healthcare Clinical Science, UK) for clinical scientist support, Dr. Tim Smith for biologist support, Mr. Gordon Buchan for technician support, Ms Bolanle Brikinns for patient recruitment support, Ms Dawn Younie for logistic support and Prof. Andrew M. Blamire for advice on MRS. The authors would also like to thank Mr Roger Bourne and Ms Mairi Fuller for providing access to the patients. Funding: This study has received funding from Friends of Aberdeen and North Centre for Haematology, Oncology and Radiotherapy (ANCHOR) (RS2015 004). Sai Man Cheung’s PhD study was jointly supported by Elphinstone scholarship, Roland Sutton Academic Trust and John Mallard scholarshipPeer reviewedPublisher PD

Peri-tumoural spatial distribution of lipid composition and tubule formation in breast cancer

[Acknowledgements:] The authors would like to thank Dr. Matthew Clemence (Philips Healthcare Clinical Science, UK) for clinical scientist support, Ms Bolanle Brikinns for patient recruitment support and Ms Dawn Younie for logistic support. [Funding:] This project was funded by NHS Grampian Endowment Research Fund (15/1/052). Sai Man Cheung’s PhD study was jointly supported by Elphinstone scholarship, Roland Sutton Academic Trust and John Mallard scholarship and is currently funded by Cancer Research UK (C68628/A28312). Nicholas Senn’s PhD study was supported by BBSRC EASTBIO scholarship (1654748). The funding sources were not involved in the study design, in the collection, analysis and interpretation of data, in the writing of the report nor in the decision to submit the article for publicationPeer reviewedPublisher PD

Spatial heterogeneity of peri-tumoural lipid composition in postmenopausal patients with oestrogen receptor positive breast cancer

Funding Information: This project was funded by Friends of Aberdeen and North Centre for Haematology, Oncology and Radiotherapy (ANCHOR) (RS2016 004). Sai Man Cheung’s PhD study was jointly supported by Elphinstone scholarship, Roland Sutton Academic Trust and John Mallard scholarship and is currently funded by Cancer Research UK (C68628/A28312). The funding sources were not involved in the study design, in the collection, analysis and interpretation of data, in the writing of the report nor in the decision to submit the article for publication.Peer reviewe

Incidence of male breast cancer in Scotland over a twenty-five-year period (1992 - 2017)

Acknowledgements This work was supported by the University of Aberdeen Development Trust. AH and MG participated in the Arcadia Aberdeen STEM Summer Research Programme 2019.Peer reviewedPostprin

Peri-Tumoural Lipid Composition and Hypoxia for Early Immune Response to Neoadjuvant Chemotherapy in Breast Cancer

The authors would like to thank Matthew Clemence (Philips Healthcare Clinical Science, UK) for clinical scientist support; Erica Banks and Alison McKay for patient recruitment support; Teresa Morris and Dawn Younie for logistics support; Beverly McLennan, Nichola Crouch, Laura Reid, Mike Hendry for radiographer support; and Gordon Urquhart for providing access to the patients.Peer reviewe

Towards detection of early response in neoadjuvant chemotherapy of breast cancer using Bayesian intravoxel incoherent motion

IntroductionThe early identification of good responders to neoadjuvant chemotherapy (NACT) holds a significant potential in the optimal treatment of breast cancer. A recent Bayesian approach has been postulated to improve the accuracy of the intravoxel incoherent motion (IVIM) model for clinical translation. This study examined the prediction and early sensitivity of Bayesian IVIM to NACT response.Materials and methodsSeventeen female patients with breast cancer were scanned at baseline and 16 patients were scanned after Cycle 1. Tissue diffusion and perfusion from Bayesian IVIM were calculated at baseline with percentage change at Cycle 1 computed with reference to baseline. Cellular proliferative activity marker Ki-67 was obtained semi-quantitatively with percentage change at excision computed with reference to core biopsy.ResultsThe perfusion fraction showed a significant difference (p = 0.042) in percentage change between responder groups at Cycle 1, with a decrease in good responders [−7.98% (−19.47–1.73), n = 7] and an increase in poor responders [10.04% (5.09–28.93), n = 9]. There was a significant correlation between percentage change in perfusion fraction and percentage change in Ki-67 (p = 0.042). Tissue diffusion and pseudodiffusion showed no significant difference in percentage change between groups at Cycle 1, nor was there a significant correlation against percentage change in Ki-67. Perfusion fraction, tissue diffusion, and pseudodiffusion showed no significant difference between groups at baseline, nor was there a significant correlation against Ki-67 from core biopsy.ConclusionThe alteration in tumour perfusion fraction from the Bayesian IVIM model, in association with cellular proliferation, showed early sensitivity to good responders in NACT.Clinical trial registrationhttps://clinicaltrials.gov/ct2/show/NCT03501394, identifier NCT03501394

Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer

Abstract: Stromal tumor-infiltrating lymphocytes (sTILs) are important prognostic and predictive biomarkers in triple-negative (TNBC) and HER2-positive breast cancer. Incorporating sTILs into clinical practice necessitates reproducible assessment. Previously developed standardized scoring guidelines have been widely embraced by the clinical and research communities. We evaluated sources of variability in sTIL assessment by pathologists in three previous sTIL ring studies. We identify common challenges and evaluate impact of discrepancies on outcome estimates in early TNBC using a newly-developed prognostic tool. Discordant sTIL assessment is driven by heterogeneity in lymphocyte distribution. Additional factors include: technical slide-related issues; scoring outside the tumor boundary; tumors with minimal assessable stroma; including lymphocytes associated with other structures; and including other inflammatory cells. Small variations in sTIL assessment modestly alter risk estimation in early TNBC but have the potential to affect treatment selection if cutpoints are employed. Scoring and averaging multiple areas, as well as use of reference images, improve consistency of sTIL evaluation. Moreover, to assist in avoiding the pitfalls identified in this analysis, we developed an educational resource available at www.tilsinbreastcancer.org/pitfalls

Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group

Funder: U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)Funder: National Center for Research Resources under award number 1 C06 RR12463-01, VA Merit Review Award IBX004121A from the United States Department of Veterans Affairs Biomedical Laboratory Research and Development Service, the DOD Prostate Cancer Idea Development Award (W81XWH-15-1-0558), the DOD Lung Cancer Investigator-Initiated Translational Research Award (W81XWH-18-1-0440), the DOD Peer Reviewed Cancer Research Program (W81XWH-16-1-0329), the Ohio Third Frontier Technology Validation Fund, the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering and the Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University.Funder: Susan G Komen Foundation (CCR CCR18547966) and a Young Investigator Grant from the Breast Cancer Alliance.Funder: The Canadian Cancer SocietyFunder: Breast Cancer Research Foundation (BCRF), Grant No. 17-194Abstract: Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring